Now available as a docker-hub pull:
$ docker pull fishcorn/dvtb-container $ [NV_GPU=<your_gpu_id>] nvidia-docker run -ti \ --name dvtb \ -e DISPLAY \ -v /tmp/.X11-unix:/tmp/.X11-unix \ -v /path/to/a/workspace:/home/developer/work \ fishcorn/dvtb-container
Note that the
developer user has
uid:gid == 1000:1000, which will map to the current user for most single-user Debian/Ubuntu systems, but for other uid/gid combinations you'd have to rebuild the image (see below).
I know there are ways to remap the uid/gid, but I just haven't included one because of time. Feel free to issue a pull request to enable this though.
This is a docker container that encapsulates all of the annoying steps to get yosinski/deep-visualization-toolbox working.
See http://yosinski.com/deepvis for general information, along with a video, and https://github.com/yosinski/deep-visualization-toolbox for the actual software.
This container is mostly to get things working easily, and will let you run this with X windows, even though it's in a container. The last bit is enabled with ideas from this excellent blog post by Fábio Rehm.
Change Dockerfile so that the uid and gid match yours, then build this container with
$ nvidia-docker build -t <name_or_tag> .
Run this container with
$ [NV_GPU=<your_gpu_id>] nvidia-docker run -ti \ --name dvtb \ -e DISPLAY \ -v /tmp/.X11-unix:/tmp/.X11-unix \ -v /path/to/a/workspace:/home/developer/work \ <name_or_tag>
Again, thanks to Fábio Rehm for doing the X Windows groundwork.
I welcome pull requests to get this working better/more efficiently.